San Francisco, June 3-6, 2019 (Updated continuously)
Just now the Snowflake Summit is happening. Great Announcements – Today in Public Preview available:
Last 12 month Innovations:

Where we are going? Major Investment Areas

Core DWH Performance:
Huge concurrency, Low Latency (a lot of small queries)
Large and ad hoc queries, Data Science
Core DWH Security
oAuth. AAD, ..
Better Touch-points with eternal Systems
Core DWH Rich Experience
Worksheets 3.0
Query Editor IntelliSense (Numeracy) , Schema Browser, Visual queries by column (histogram, data profiling at zero coding) , sharing of query with team members
Credential-less Stages
Separation of stage from physical touch point, storage integration => no longer passing of credentials, it allows separation of roles.

Snowpipe Auto-Ingest

Automatically load data in to snowflake
Your data should not be stuck in Snowflake (unload of Data should be simple)

Kafka Connector

Table Streams & scheduled Tasks

External Tables
Connect your existing Data Lake
Hive-Meta-Store Integration
Listeners replays Meta Data changes

Materialized Views on External Tables

Database Replication (in Q3/2019)
80 % of the Cloud Customer go for a multi cloud provider strategy

Link/replicate Databases from AWS to Azure and from Azure to AWS (Primary and secondary Databases). From Account to Account and cross Region, cross Cloud on transnational database level.
Global Snowflake / Fail over by connection string
Standard and personalized shares


Strategic partnership with Google Cloud!
In Q3 / 2019 in Preview

If you do not have a data lake strategy yet, SnowfLAKE can be your Data Lake or extend your existing one.. Hadoop was like going back to stone-hedge in terms of performance, that’s why we created SnowfLAKE.





Views: 227